





'''simple docstring'''

from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxSeqaSeqConfigWithPast
from ...utils import logging


lowercase__		:     List[Any]			=							logging.get_logger(__name__)

lowercase__		:     str			=							{
    'google/umt5-small': 'https://huggingface.co/google/umt5-small/resolve/main/config.json',
    # See all umt5 models at https://huggingface.co/models?filter=umt5
}
class 							__lowerCAmelCase	(       __magic_name__					):






       """simple docstring"""
       _snake_case      :	str									=       'umt5'
       _snake_case      :	Dict									=       ['past_key_values']





       def __init__(				self  :						Union[str, Any]			,					lowerCAmelCase__  :						Optional[Any]=250112			,					lowerCAmelCase__  :						Optional[int]=512			,					lowerCAmelCase__  :						Optional[int]=64			,					lowerCAmelCase__  :						Optional[int]=1024			,					lowerCAmelCase__  :						Optional[int]=8			,					lowerCAmelCase__  :						Dict=None			,					lowerCAmelCase__  :						List[str]=6			,					lowerCAmelCase__  :						Tuple=32			,					lowerCAmelCase__  :						Any=128			,					lowerCAmelCase__  :						int=0.1			,					lowerCAmelCase__  :						int=1e-6			,					lowerCAmelCase__  :						Union[str, Any]=1.0			,					lowerCAmelCase__  :						Union[str, Any]="gated-gelu"			,					lowerCAmelCase__  :						Optional[Any]=True			,					lowerCAmelCase__  :						List[Any]=True			,					lowerCAmelCase__  :						Any="T5Tokenizer"			,					lowerCAmelCase__  :						Optional[int]=True			,					lowerCAmelCase__  :						Dict=0			,					lowerCAmelCase__  :						str=1			,					lowerCAmelCase__  :						int=0			,					**lowerCAmelCase__  :						Dict			,					)       ->	int:

            '''simple docstring'''




            super().__init__(
                is_encoder_decoder=lowerCAmelCase__			,					tokenizer_class=lowerCAmelCase__			,					tie_word_embeddings=lowerCAmelCase__			,					pad_token_id=lowerCAmelCase__			,					eos_token_id=lowerCAmelCase__			,					decoder_start_token_id=lowerCAmelCase__			,					**lowerCAmelCase__			,					)
            _UpperCamelCase							       =			vocab_size
            _UpperCamelCase							       =			d_model
            _UpperCamelCase							       =			d_kv
            _UpperCamelCase							       =			d_ff
            _UpperCamelCase							       =			num_layers
            _UpperCamelCase							       =			(
                num_decoder_layers if num_decoder_layers is not None else self.num_layers
            )  # default = symmetry
            _UpperCamelCase							       =			num_heads
            _UpperCamelCase							       =			relative_attention_num_buckets
            _UpperCamelCase							       =			relative_attention_max_distance
            _UpperCamelCase							       =			dropout_rate
            _UpperCamelCase							       =			layer_norm_epsilon
            _UpperCamelCase							       =			initializer_factor
            _UpperCamelCase							       =			feed_forward_proj
            _UpperCamelCase							       =			use_cache

            _UpperCamelCase							       =			self.feed_forward_proj.split('''-'''	)
            _UpperCamelCase							       =			act_info[-1]
            _UpperCamelCase							       =			act_info[0] == '''gated'''

            if len(lowerCAmelCase__	) > 1 and act_info[0] != "gated" or len(lowerCAmelCase__	) > 2:
                 raise ValueError(
                     f"""`feed_forward_proj`: {feed_forward_proj} is not a valid activation function of the dense layer."""
                     '''Please make sure `feed_forward_proj` is of the format `gated-{ACT_FN}` or `{ACT_FN}`, e.g. '''
                     '''\'gated-gelu\' or \'relu\''''	)

            if feed_forward_proj == "gated-gelu":
                 _UpperCamelCase							       =			'''gelu_new'''





       @property
       def snake_case__		(				self  :						Tuple	)       ->	Optional[Any]:

            '''simple docstring'''




            return self.d_model





       @property
       def snake_case__		(				self  :						List[str]	)       ->	List[Any]:

            '''simple docstring'''




            return self.num_heads







       @property
       def snake_case__		(				self  :						Optional[int]	)       ->	Any:

            '''simple docstring'''




            return self.num_layers

class 							__lowerCAmelCase	(       __magic_name__					):






       """simple docstring"""





       @property
       # Copied from transformers.models.t5.configuration_t5.T5OnnxConfig.inputs
       def snake_case__		(				self  :						Dict	)       ->	Mapping[str, Mapping[int, str]]:

            '''simple docstring'''




            _UpperCamelCase							       =			{
                '''input_ids''': {0: '''batch''', 1: '''encoder_sequence'''},
                '''attention_mask''': {0: '''batch''', 1: '''encoder_sequence'''},
            }
            if self.use_past:
                 _UpperCamelCase							       =			'''past_encoder_sequence + sequence'''
                 _UpperCamelCase							       =			{0: '''batch'''}
                 _UpperCamelCase							       =			{0: '''batch''', 1: '''past_decoder_sequence + sequence'''}
            else:
                 _UpperCamelCase							       =			{0: '''batch''', 1: '''decoder_sequence'''}
                 _UpperCamelCase							       =			{0: '''batch''', 1: '''decoder_sequence'''}

            if self.use_past:
                 self.fill_with_past_key_values_(lowerCAmelCase__			,					direction='''inputs'''	)

            return common_inputs





       @property
       # Copied from transformers.models.t5.configuration_t5.T5OnnxConfig.default_onnx_opset
       def snake_case__		(				self  :						Tuple	)       ->	int:

            '''simple docstring'''




            return 13







       @property
       def snake_case__		(				self  :						Optional[Any]	)       ->	float:

            '''simple docstring'''




            return 5e-4




from abc import ABC, abstractmethod
from argparse import ArgumentParser





class     lowerCAmelCase__     (				SCREAMING_SNAKE_CASE_			):


		'''simple docstring'''






		@staticmethod
		@abstractmethod
		def   _snake_case       (       snake_case__     :     ArgumentParser		)      ->	Tuple:
				raise NotImplementedError()



		@abstractmethod
		def   _snake_case       (       self     :     Optional[Any]		)      ->	Optional[Any]:
				raise NotImplementedError()